Protocol: A mixed methods evaluation of an IPS program to increase employment and well-being for people with long-term experience of complex barriers in Vancouver’s downtown and DTES
Bibliographic record
Abstract
BACKGROUND: Employment improves mental health and well-being by providing financial security, daily structure, a sense of identity and purpose, and social engagement. However, securing and sustaining employment is exceptionally challenging for vulnerable populations who experience persistent and multiple barriers, such as mental illness, homelessness, food and housing insecurity, and marginalization. Evidence-based supported employment programs, most notably individual placement and support (IPS) are becoming a more common approach for addressing the needs of these high-risk individuals. The aim of this paper is to outline the protocol for evaluating an IPS program in Vancouver's downtown and Downtown Eastside (DTES). METHODS AND DESIGN: This prospective quasi-experimental study of persons with persistent and multiple barriers to employment will use a mixed-methods approach for evaluating a novel IPS program. The evaluation will consist of survey packages and interviews that will capture outcomes related to employment and well-being, as well as the experiential process of receiving individualized and integrated supports through the IPS program. A mixed-methods approach is appropriate for this study as quantitative data will provide an objective assessment of program impacts on employment and well-being outcomes over time, while qualitative data will provide an in-depth understanding of continued barriers and experiences. DISCUSSION: The results from this evaluation will contribute evidence within a local British Columbian (BC) context that may increase access to meaningful employment for those with long-term experience of complex barriers to employment. Further, the findings will support continued improvements, and guide decision-making around practices and policy for future implementation of IPS and employment supports across BC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.081 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.039 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".